Integrated Wearable Noise Dosimeter

ABSTRACT

Systems and methods are described that may provide audio information about an environment around a wearable device. Such audio information may be correlated with other biometric data to provide physiological information, e.g. regarding a wearer of the wearable device. For example, an illustrative method includes receiving an audio signal via a microphone of a wearable device and rectifying the audio signal with a peak detector. The method further includes amplifying the rectified signal with a logarithmic amplifier and causing an analog to digital converter (ADC) to sample the logarithmic signal. The method also includes causing the ADC to convert the sampled logarithmic signal to a digital output and storing the digital output in a memory of the wearable device. In some embodiments, the method includes transmitting the digital output to a computing device, which may correlate the digital output with other biometric data.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of, and claims the benefit ofpriority from, U.S. patent application Ser. No. 14/698,155, filed Apr.28, 2015, which is hereby incorporated herein by reference in itsentirety.

BACKGROUND

An environmental monitoring device may provide information about a soundpressure level of an environment around the monitoring device.

SUMMARY

In a first aspect, a system is provided. The system includes amicrophone configured to provide an audio signal and a rectifiercommunicatively coupled to the microphone. The system also includes alogarithmic amplifier communicatively coupled to the rectifier. Acombination of the logarithmic amplifier and the rectifier is configuredto provide a rectified logarithmic signal based on a mathematical logfunction and the audio signal. The system additionally includes ananalog to digital converter (ADC) communicatively coupled to thelogarithmic amplifier. The ADC is configured to sample the rectifiedlogarithmic signal and provide a digital output based on the sampledrectified logarithmic signal. The system further includes a controllerthat includes a memory and a processor. The controller is configured tocarry out instructions. The instructions include, at predetermined timeintervals, causing the ADC to sample the rectified logarithmic signaland storing the digital output in the memory. The instructions alsoinclude transmitting the digital output to a computing device. Thecomputing device is configured to correlate the digital output withother biometric data.

In a second aspect, a system is provided. The system includes amicrophone configured to provide an audio signal, a logarithmicamplifier communicatively coupled to the microphone, a rectifiercommunicatively coupled to the logarithmic amplifier, an analog todigital converter (ADC) communicatively coupled to the rectifier, and acontroller. The logarithmic amplifier is configured to provide alogarithmic signal based on a mathematical log function and the audiosignal. The rectifier is configured to provide a rectified signal basedon the logarithmic signal. The ADC is configured to sample the rectifiedsignal and provide a digital output based on the sampled rectifiedsignal. The controller includes a memory and a processor. The controlleris configured to carry out instructions. The instructions include, atpredetermined time intervals, causing the ADC to sample the rectifiedsignal and storing the digital output in the memory. The instructionsalso include transmitting the digital output to a computing device. Thecomputing device is configured to correlate the digital output withother biometric data.

In a third aspect, a system is provided. The system includes amicrophone configured to provide an audio signal, a rectifiercommunicatively coupled to the microphone, an analog to digitalconverter (ADC) communicatively coupled to the rectifier, and acontroller. The rectifier is configured to provide a rectified signalbased on the audio signal. The ADC is configured to sample the rectifiedsignal and provide a digital output based on the sampled rectifiedsignal. The controller includes a memory and a processor. The controlleris configured to carry out instructions. The instructions include, atpredetermined time intervals, causing the ADC to sample the rectifiedsignal and storing the digital output in the memory. The instructionsalso include providing a logarithmic output based on a mathematical logfunction and the digital output. The instructions further includetransmitting the digital output to a computing device, wherein thecomputing device is configured to correlate the digital output withother biometric data.

In a fourth aspect, a method is provided. The method includes receivingan audio signal via a microphone of a wearable device and rectifying theaudio signal with a rectifier to provide a rectified signal. Therectifier includes a peak detector. The method further includesamplifying the rectified signal with a logarithmic amplifier to providea logarithmic signal based on a mathematical log function and therectified signal. The method also includes causing an analog to digitalconverter (ADC) to sample the logarithmic signal. The method yet furtherincludes causing the ADC to convert the sampled logarithmic signal to adigital output. The method additionally includes storing the digitaloutput in a memory of the wearable device. The method also includestransmitting the digital output to a computing device. The computingdevice is configured to correlate the digital output with otherbiometric data.

Other aspects, embodiments, and implementations will become apparent tothose of ordinary skill in the art by reading the following detaileddescription, with reference where appropriate to the accompanyingdrawings.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1A illustrates a system, according to an example embodiment.

FIG. 1B illustrates a system, according to an example embodiment.

FIG. 1C illustrates a system, according to an example embodiment.

FIG. 2 illustrates a schematic block diagram of an environmentalmonitoring system, according to an example embodiment.

FIG. 3 illustrates a wearable device, according to an exampleembodiment.

FIG. 4A illustrates a device, according to an example embodiment.

FIG. 4B illustrates a device, according to an example embodiment.

FIG. 5 illustrates a system, according to an example embodiment.

FIG. 6 illustrates a method, according to an example embodiment.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying figures, which form a part hereof. In the figures, similarsymbols typically identify similar components, unless context dictatesotherwise. The illustrative embodiments described in the detaileddescription, figures, and claims are not meant to be limiting. Otherembodiments may be utilized, and other changes may be made, withoutdeparting from the scope of the subject matter presented herein. It willbe readily understood that the aspects of the present disclosure, asgenerally described herein, and illustrated in the figures, can bearranged, substituted, combined, separated, and designed in a widevariety of different configurations, all of which are explicitlycontemplated herein.

I. Overview

The present disclosure discloses embodiments in which a device isconfigured to record data related to an acoustic environment around thedevice. For example, a sound pressure level (SPL) of the environmentaround the device may be recorded and tracked over a long period of time(e.g. weeks, months, and/or years). The SPL data may relate to aparticular environment (e.g. a room or an area in the case of a staticdevice) and/or a local environment around the device (e.g. near a wearerof a wearable device). SPL data may be useful to track medicalconditions such as breathing, sleep apnea, or environmental conditions,such as ambient noise levels in a work environment, at concerts, etc. Inan example embodiment, the SPL data may be detected and processed usinga wearable biotelemetry device. Alternative uses may include homesecurity or environmental monitoring systems.

In an example embodiment, a wearable device may be configured to measureand record SPL data without the possibility of capturing intelligibleacoustic content, e.g. without recording actual conversations or otherrecognizable sounds. For example, the wearable device may include asmall form factor microphone. The microphone may be a device thattransduces sounds, e.g. pressure waves in air, into an electricalsignal. The microphone may operate based on electromagnetic induction,piezoelectricity, or a change in capacitance, among other modes ofoperation. The signal produced by the microphone may be amplified by apre-amplifier circuit (which may be a component of the microphone). Insome embodiments, however, a pre-amplifier is not present.

The signal from the pre-amplifier circuit may be passed through arectifying circuit that may modify the signal. Rectifying circuits mayinclude an envelope detector, a peak detector, and/or a trough detector,among other types of rectifying circuits. For example, a peak detectormay include a rectifying circuit that includes at least one capacitiveelement. Furthermore, the peak detector may be configured to provide anoutput signal based on the peak amplitude of the unprocessed signal.

The rectifying circuit may produce a relatively slowly changing voltagethat may represent the instantaneous amplitude of the audio waveform.The response time of the circuit is slow enough such that individualsyllables of speech are detectable, but not identifiable. In an exampleembodiment, the response time of the circuit may be configured todistinguish a respiration rate (or snoring) from conversation or otheridentifiable sounds.

Within the scope of the present disclosure, the rectifying circuit mayinclude analog signal processing hardware. By performing the signalrectification using analog hardware (versus software or digital signalprocessing), security and privacy concerns may be reduced or eliminated.For example, it may be more difficult to obtain identifiable orrecognizable audio signals when the recorded signals are passedsubstantially directly to signal processing hardware without interveningdigital signal handling.

Before and/or after the signal is rectified, the signal may be passedthrough a logarithmic amplifier (Log Amp). The Log Amp may be configuredto convert a voltage signal to decibels. The Log Amp may additionally oralternatively include filters with controlled response to providedifferent “weightings” to the detected audio based on, for instance, thefrequency components of the signal. For example, the output of the LogAmp may convert and/or translate the voltage signal to a signal that mayrelate to decibel A-weighting (dBA).

In an example embodiment, decibel A-weighting may be applied to thelogarithmic signal, which may convert the logarithmic signal to arecognized measure of SPL. Specifically, dBA has been adopted as anenvironmental noise measurement standard and may offer a comparisonbetween the detected audio signals and well-known real-world noisesources (rock concert, airplane takeoff, etc.). Other frequency-relatedweightings are possible, including, but not limited to, B-, C-, D-, andZ-weightings.

The output of the Log Amp may be passed to an analog to digitalconverter (ADC). The output of the ADC may be saved locally and/ortransmitted to cloud storage and/or cloud computing devices. Uploadingto cloud storage and/or cloud computing devices may occur in “realtime.” Alternatively or additionally, uploading could occur periodicallyat predetermined time intervals, or at other times.

The microphone, rectifier, the Log Amp, and/or other components of thesystem may be configured to handle audio signals at +20 dBA or quieter.For example, the system may be configured to capture breathing, gasping,or talking noises from a wearer of the wearable biotelemetry device.Accordingly, the system may include components configured to reduce orminimize signal noise, e.g. low noise preamplifiers, noise filters, etc.Additionally or alternatively, some or all of the components of thesystem may be configured to handle relatively loud audio signals (e.g.+120 dBA or louder). Accordingly, the system may be configured to handlea large range of SPL values, such as multiple signal gain and/orattenuation stages.

Example embodiments may include several different variations regardingthe order of how signals are processed in the system. For instance, thesignal may pass through the Log Amp before passing through the rectifiercircuit, or vice versa. Other combinations of rectification,amplification, and/or filtering may be implemented under the scope ofthe present disclosure.

Other processing and/or sampling may be performed on the signal usinghardware or software. For instance, an analog to digital converter (ADC)may be configured to sample the signal as sampled data. The signal maybe sampled at frequencies such as 50 Hz or 60 Hz, but other samplingfrequencies are possible. The sampled data may be stored locally, forexample in system memory. Alternatively or additionally, the sampleddata may be uploaded to a network (e.g. a cloud server), which may storeor aggregate data about noise levels.

In an example embodiment, a system may include a microphone, apre-amplifier, a peak detector, a log amplifier, and an analog todigital converter (ADC). In another example embodiment, a system mayadditionally or alternatively include a trough detector. The system mayinclude hardware and/or software configured to perform the functions ofa log amplifier. Additionally or alternatively, further functions (e.g.filtering) may be performed using further signal processing hardwareand/or software.

In an example embodiment, the sampled data may be correlated with otherbiometric data or parameters. For example, a sleep apnea condition maybe diagnosed and/or treated by correlating the sampled SPL and/or dBAdata with respiration and/or movement data of the wearer of abiotelemetry device. Alternatively, for example to measure sleepquality, the sampled SPL and/or dBA data may be correlated with otherdata such as blood pressure, heart rate, blood oxygen saturation,respiration, and/or movement. In another example related to measuringstress level, the sampled SPL and/or dBA data may be correlated withheart rate, blood pressure, and/or galvanic skin response. In yetanother example, mental health and/or general health issues related tospeech may be tracked using the sampled SPL and/or dBA data inconjunction with other data such as movement. Many other datacorrelations may be made with the sampled SPL data. The datacorrelations may be performed by a computing device, which may be awearable biotelemetry device or another computing device, such as acloud computing network.

II. System Examples

FIG. 1A illustrates a system 100, according to an example embodiment.System 100 includes a microphone 102 configured to provide an audiosignal. That is, the microphone 102 may be configured to convert anacoustic sound or a sound pressure level into the audio signal, whichmay be an electrical signal. The microphone 102 may be one of, or anycombination of, a fiber optic microphone, a dynamic microphone, acondenser microphone, an electret condenser microphone, a ribbonmicrophone, a MEMS microphone, and/or a piezoelectric microphone. Othertypes of microphones are contemplated herein. The microphone 102 may beintegrated into another electronic device, e.g. a smartphone or awearable computing device. Alternatively or additionally, the microphone102 may be an externally coupled to another device, e.g. via a cable.

The system 100 may include a pre-amplifier 104. The pre-amplifier 104may amplify an electrical signal from the microphone 102. In an exampleembodiment, the pre-amplifier 104 may apply gain to the electricalsignal from the microphone 102. The pre-amplifier 104 may include one ormore gain stages. In an example embodiment, the pre-amplifier 104 may beincorporated into, and/or housed with, the microphone 102. In otherembodiments, the pre-amplifier 104 is not included in the system 100.

The system 100 also includes a rectifier 106 communicatively coupled tothe microphone 102 or the pre-amplifier 104. The rectifier 106 mayconvert a varying or alternating current into a direct current. Therectifier 106 may be a stand-alone part or the rectifier may includeelectronic components arranged in an electrical circuit. For example,the rectifier 106 may include a silicon diode, a thyristor, a crystalrectifier, or another type of rectifier. In an example embodiment, therectifier 106 includes a single-phase, half-wave rectifier circuit.However, other rectifier circuits are contemplated herein, e.g. asingle-phase, full-wave rectifier circuit. In an example embodiment, therectifier 106 may include a filter circuit. Thus, in such situations,the rectifier 106 may provide filtering and/or other types of signalprocessing to the audio signal.

The rectifier 106 is configured to provide a rectified signal based onthe audio signal. In an example embodiment, the rectifier 106 includes apeak-hold circuit, which may also be termed a peak detector or anenvelope detector. The peak detector may take as its input the audiosignal provided by the microphone 102 or pre-amplifier 104 and mayoutput the peak output voltage of the audio signal. In an exampleembodiment, the peak detector may include adjustable characteristics,such as attack time and/or decay time. The peak detector may beconfigured to “hold” a peak voltage for a much longer time than the peakvoltage may exist in the input audio signal. The peak detector circuitmay include at least one operational amplifier, a diode, and acapacitor. Additionally or alternatively, the peak detector circuit mayinclude a point contact device. Other types of circuits configured torectify a varying electrical signal and/or track a peak amplitude of thevarying electrical signal are contemplated herein.

The system 100 also includes a logarithmic amplifier 108 communicativelycoupled to the rectifier 106. The logarithmic amplifier 108 isconfigured to provide a logarithmic signal based on a mathematical logfunction and the rectified signal from the rectifier 106. Namely, thelogarithmic amplifier 108 may provide an output voltage that is amultiple of the natural logarithm of the input voltage. The logarithmicamplifier 108 may include one or more amplification or gain stages, e.g.four 30-dB amplification stages. The logarithmic amplifier 108 may besimilar or identical to a Maxim AN 36211 or a Texas Instruments TL441.In an example embodiment, the logarithmic amplifier 108 includes abaseband logarithmic amplifier or a demodulating logarithmic amplifier.

The system 100 may include the rectifier 106 and logarithmic amplifier108 in various arrangements. For example, the signal flow may go throughthe rectifier 106 and then the logarithmic amplifier 108, or vice versa.In an example embodiment, a combination of the rectifier 106 and thelogarithmic amplifier 108 may provide a signal that is both rectifiedand modified (e.g. multiplied) based on a mathematical log function. Insuch a scenario, the provided signal may be a rectified logarithmicsignal.

The system 100 also includes an analog to digital converter (ADC) 110communicatively coupled to the logarithmic amplifier 108. The ADC 110 isconfigured to convert the continuous time, continuous amplitude signalfrom the logarithmic amplifier 108 to a discrete time, discreteamplitude digital signal. Namely, the ADC 110 is configured to samplethe rectified logarithmic signal and provide a discrete digital outputproportional to the sampled rectified logarithmic signal. The discretedigital output may include a conversion error at least based on the bitresolution of the ADC 110. The ADC 110 may have a 16-bit resolution,however other resolutions are possible. The sampling rate of the ADC 110may be 10-100 samples per second, however other sampling rates arepossible.

The system 100 may be configured to detect and record sounds as quiet as+20 dBA (e.g., breathing) and as loud as +120 dBA (e.g., a concert).Thus, system 100 may be configured and/or designed with low-noisecomponents and multiple gain stages to provide a low noise floor andwide dynamic range.

Other arrangements of some or all of the elements of system 100 arepossible. For example, FIGS. 1B and 1C illustrate two such otherarrangements. FIG. 1B illustrates a system 120, according to an exampleembodiment. System 120 may include a microphone 102 and a pre-amplifier104 arranged similarly to system 100 as illustrated and described inreference to FIG. 1A. System 120 may include a logarithmic amplifier 108communicatively coupled to the microphone 102 and/or the pre-amplifier104. The logarithmic amplifier 108 may be configured to provide alogarithmic signal based on a mathematical log function and the audiosignal, as described above.

System 120 may further include a trough detector 122 communicativelycoupled to the logarithmic amplifier 108. The trough detector 122 may bea rectifier configured to track the audio signal and hold a voltagelevel based on a minimum level, magnitude, and/or amplitude of the audiosignal. The system 120 may also include the ADC 110 communicativelycoupled to the trough detector 122.

In some embodiments, the system 120 may include a trough detector 122 ora peak detector based on a polarity of the logarithmic amplifier 108.Additionally or alternatively, the rectifier 106 and/or the troughdetector 122 may include a peak excursion detector. Other signalprocessing devices configured to modify a sound and provide outputsignal, such that the output signal is unidentifiable or untraceable toone or more people who produced the sound, are considered herein.

As a further alternative, FIG. 1C illustrates a system 140, according toan example embodiment. System 140 may include a microphone 102, apre-amplifier 104, and a rectifier 106 with a similar arrangement asthat in system 100, illustrated and described in reference to FIG. 1A.System 140 may also include the ADC 110 communicatively coupled to therectifier 106.

System 140 may include a digitized output of the ADC 110 being handled,modified, and/or processed by a computer according to softwareinstructions 142. The software instructions 142 may be stored asnon-transitory computer readable media. Further, software instructions142 may be stored in a memory and the software instructions 142 may beexecuted by a processor. The computer may modify the digitized output ofthe ADC 110 by performing one or more functions according to thesoftware instructions 142. The one or more functions may include alogarithmic multiplication. In other words, the software instructions142 and processor may be configured to provide a logarithmicamplification of the digitized signal from the ADC 110. The softwareinstructions 142 may be configured to carry out further functions on thedigitized signal.

It is understood that other combinations of analog and/or digital signalprocessing stages, components, or other elements are possible within thescope of this disclosure.

FIG. 2 illustrates a schematic block diagram of an environmentalmonitoring system 200, according to an example embodiment. Theenvironmental monitoring system 200 may include some or all of the sameelements as systems 100, 120, and/or 140, as illustrated and describedin reference to FIGS. 1A, 1B, and 1C, respectively. In an exampleembodiment, environmental monitoring system 200 includes a microphone202, a pre-amplifier 204, a rectifier 206, a logarithmic amplifier 208,and an ADC 210, which may be communicatively coupled in a seriesarrangement. Such an arrangement of elements may operable to provide adigitized signal that relates to an acoustic environment around theenvironmental monitoring system 200. As described above, otherarrangements of the microphone 202, pre-amplifier 204, rectifier 206,logarithmic amplifier 208, and/or the ADC 210 are possible.

The environmental monitoring system 200 may also include other sensors212. The other sensors 212 may include one or more sensors configured tomeasure, monitor, qualify and/or quantify various biometric data. Manytypes of biometric data are contemplated within the scope of thisdisclosure. For example, the other sensors 212 may be configured tomeasure blood pressure, heart rate, galvanic skin response, respiration,analyte concentration, movement, blood oxygen saturation, or otherbiometric data.

The environmental monitoring system 200 may further include a userinterface 214. The user interface 214 may include a display, atouchscreen, one or more indicator lights, or another type of interfaceconfigured to provide information to a user and/or to obtain input froma user. In an example embodiment, the user interface 214 may include atouchscreen display that provides information indicative of the soundpressure level of the environment around the environmental monitoringsystem 200.

The environmental monitoring system 200 may include a communicationinterface 216. The communication interface 216 may be operable toprovide a wired and/or wireless connection to another computing deviceand/or a computing network, e.g. the Internet and/or a cloud computingsystem. In an example embodiment, the communication interface 216 may bea wireless network interface controller, which may interact with awireless network via a communication protocol such as IEEE 802.11,ZIGBEE, and/or BLUETOOTH.

The environmental monitoring system 200 may further include a controller222. The controller 222 may include a memory 218 and a processor 220.The controller 222 is configured to carry out instructions. Theinstructions may include, at predetermined time intervals, causing theADC 210 to sample the logarithmic signal. For example, the controller222 may cause the ADC 210 to sample the logarithmic signal at a samplingrate, e.g. 50 samples/second. The instructions may also include storingthe digital output from the ADC 210 in the memory 218.

The instructions may further include transmitting the digital output toa computing device. In an example embodiment, the transmitting mayinclude transmitting the digital output to another computing device viacommunication interface 216. In another embodiment, the transmitting mayinclude transmitting the digital output to the controller 222. In bothscenarios, the computing device may be configured to correlate thedigital output with other biometric data. The other biometric data mayinclude any data obtained by the other sensors 212. Additionally oralternatively, the other biometric data may include data calculatedand/or inferred by a computing device based on one or more further typesof biometric data.

FIG. 3 illustrates a wearable device 300, according to an exampleembodiment. The wearable device 300 may be worn around an arm, similarto a watch. Alternatively or additionally, the wearable device 300 maybe worn around a neck (e.g. a necklace), and/or at other locations. Inan example embodiment, the wearable device 300 may include a face 302and a band 304. The band 304 may be operable to fasten the wearabledevice 300 to an arm and/or a wrist of a user. In the alternative, it isunderstood that band 304 may include a necklace, chain, adhesive, oranother mechanical device configured to couple the wearable device 300to a user.

The face 302 may include a display 306. The display 306 may be atouchscreen, however, other types of displays and/or indicators arecontemplated. In an example embodiment, the display 306 may provide anindication 308 to a user. The indication 308 may include informationindicative of a sound pressure level (SPL) of the environment of thewearable device 300.

In an example embodiment, the wearable device 300 may include amicrophone 310. The microphone 310 may be the microphone 102 or 202, asillustrated and described in reference to FIGS. 1A-1C and 2. Themicrophone 310 may be operable to record the SPL of an environmentaround the wearable device 300. SPL data may capture sounds made by theuser, particularly during sleep, such as gasping for breath, snoring,sneezing, wheezing, and/or other breathing sounds. Additionally, SPLdata may include sounds nearby the user, such as an ambient noise level.Sound level data may be saved by the wearable device 300 and/or uploadedto another computing device.

Any or all of the elements of environmental monitoring system 200 may beincorporated, fully or in part, into the wearable device 300. Forexample, the wearable device 300 may include other sensors configured todetect other types of biometric data, such as heart rate and bloodpressure. By combining SPL data with the other biometric data, variousinferences may be made regarding the health of a user of the wearabledevice 300.

For example, in an effort to measure sleep quality, the sampled SPL datamay be correlated with other data such as blood pressure, heart rate,blood oxygen saturation, respiration, and/or movement. That is, if SPLdata indicates gasping for breath during sleep and the user's bloodoxygen saturation is below a predetermined level, an inference may bemade that a user's sleep quality may be poor.

Furthermore, the SPL data in combination with other biometric data maybe useful to help provide health professionals with evidence to supporta particular diagnosis. As an example, if, during sleep, a) SPL dataindicates snoring and gasping for breath, b) the user's blood pressureis elevated above a predetermined level, and c) a movement rate washigh, an inference may be made that the user may be suffering from asleep apnea condition. Other health related inferences and/or diagnosesmay be made based on the SPL data as well as the SPL data in combinationwith other biometric data.

In a scenario where a user may be suffering from a medical condition,the system and methods herein may include further functions and/orinstructions configured to provide biometric feedback to a user in aneffort to provide treatment and/or alleviate symptoms related to themedical condition. In an example embodiment, biometric data obtained bythe systems and methods described herein may be used to determine asleep apnea condition. In such a scenario, the system may provide alocal notification (e.g. a subconscious or conscious alert) to “nudge”the user back into a normal sleep pattern. For example, the system maybe configured to provide audio feedback, e.g. the controller may causean audio feedback device and a speaker to state: “roll onto your side,”“insert your oral appliance,” or “please wear your CPAP device.” Othertypes of user feedback are possible, such as a vibration alert, a chime,or another type of alert.

In another example related to measuring stress level, the sampled SPLand/or dBA data may be correlated with heart rate, blood pressure,stress-related analytes, and/or galvanic skin response. In such ascenario, a correlation that suggests an elevated stress level maytrigger an indication 308 to a user of the wearable device 300. Forexample, an indication 308 such as, “Take a deep breath”, “Go for arun”, or “Practice mindfulness for 5 minutes” may be presented to theuser of the wearable device 300 via the display 306 in an effort toreduce the user's stress level.

In yet another example, mental health and/or general health issuesrelated to speech may be tracked using the sampled SPL and/or dBA datain conjunction with other data such as movement. For example, a user ofthe wearable device 300 may speak a phrase once a day, once a week, orover a different period. The sampled SPL data associated with theverbalized phrase may change over time, which may indicate a change inverbal, mental, and/or physical ability. As such, the SPL data may beused to track, diagnose, and/or evaluate the changing condition of theuser over a period of time.

It is understood that SPL data and/or other biometric data may berecorded and correlated over a variety of time periods. For instance,SPL data may be monitored and/or stored over days, weeks, months, oryears.

While FIG. 3 illustrates a wearable device 300, various elements ofenvironmental monitoring system 200 may be incorporated into other typesof devices. For example, some or all of the elements of environmentalmonitoring system 200 may be incorporated into a static device as partof a home appliance or another type of substantially fixed or staticdevice.

FIG. 4A illustrates a device 400, according to an example embodiment.Device 400 may be configured to have some or all of the functionality ofa clock radio or similar device. In an example embodiment, device 400may be placed near a bedside or another sleep environment. Device 400may include microphone 402, which may be similar or identical tomicrophone 202 as illustrated and described in reference to FIG. 2.

FIG. 4B illustrates a device 410, according to an example embodiment.Device 410 may be configured to have some or all the functionality of athermostat and/or another type of environmental monitoring device.Device 410 may include a microphone 412, which may be similar oridentical to microphone 202 as illustrated and described in reference toFIG. 2.

It is understood that environmental monitoring system 200 may take theform of, or be incorporated into, a variety of different objects,systems, and/or devices. For example, environmental monitoring system200 may be incorporated into a wall-mounted clock, a “wall-wart” plug, asmoke detector, a carbon monoxide detector, a glass-break sensor, asmartphone, a tablet, a desktop computer, or any number of otherobjects. These other possible embodiments are contemplated herein.

FIG. 5 illustrates a system 500, according to an example embodiment.System 500 may include a plurality of devices 510, which may be similaror identical to environmental monitoring system 200. Each of theplurality of devices 510 may include one or more sensors 515. The one ormore sensors 515 may be operable to provide SPL data and/or biometricdata as described elsewhere herein. Each of the plurality of devices 510may be configured to provide the SPL and/or the other biometric data toa server 530 via one or more communication networks 520. The server 530may perform some or all of the correlations between the SPL data and thebiometric data.

In an example embodiment, the plurality of devices 510 may be located inphysical proximity to one another, e.g. within the same building, near aconcert venue, within a same neighborhood or another shared environment.In such a scenario, SPL data from the plurality of devices 510 may beaggregated to obtain an average sound pressure level of the sharedenvironment. Such aggregate SPL data may be useful to monitor noiselevels at a job site and/or in a residential setting. Other uses foraggregated SPL data are possible.

III. Method Examples

FIG. 6 illustrates a method 600, according to an example embodiment. Themethod 600 includes blocks that may be carried out in any order.Furthermore, various blocks may be added to or subtracted from method600 within the intended scope of this disclosure. The method 600 maycorrespond to steps that may be carried out using any or all of thedevices and systems illustrated and described in reference to FIGS.1A-1C, 2, 3A-3B, 4A-4B, and 5.

Block 602 includes receiving an audio signal via a microphone of awearable device. The audio signal may include sounds in an environmentaround and/or near the wearable device. The audio signal may have anassociated sound pressure level, as described herein. The wearabledevice may include the wearable device 300, as illustrated and describedin relation to FIG. 3. Alternatively, the wearable device may include adifferent wearable computing device or mobile device, such as asmartphone or a tablet. The microphone may include a built-in microphoneof the wearable device. Alternatively or additionally, the microphonemay include an external microphone.

Block 604 includes rectifying the audio signal with a rectifier toprovide a rectified signal. In an example embodiment, the rectifierincludes a peak detector. The peak detector could be similar oridentical to the peak-hold circuit described in reference to system 100.

Block 606 includes amplifying the rectified signal with a logarithmicamplifier to provide a logarithmic signal based on a mathematical logfunction and the rectified signal. As described elsewhere herein, thelogarithmic amplifier may be configured to provide a logarithmic signalbased on a mathematical log function and the signal from the peak-holdcircuit.

Block 608 includes causing an analog to digital converter (ADC) tosample the logarithmic signal. In an example embodiment, a controller,such as controller 222 described in reference to FIG. 2, may control asampling trigger and/or the sampling rate of the ADC. In such ascenario, the controller may be configured to cause the ADC to samplethe logarithmic signal at a sampling rate, such as 10-100samples/second. Other sampling rates are possible.

Block 610 includes causing the ADC to convert the sampled logarithmicsignal to a digital output. Converting the sampled logarithmic signalmay include digitizing the logarithmic signal by performing a bitconversion. In an example embodiment, the ADC may include a bitresolution of 16-bits. In such a scenario, the analog logarithmic signalmay be converted into a 16-bit digitized output based on an amplitude oranother characteristic of the logarithmic signal.

Block 612 includes storing the digital output in a memory of thewearable device. In other words, the digitized output from the ADC maybe stored in a memory, such as the memory 218 of environmentalmonitoring system 200. Alternatively, the digital output need not bestored locally at the wearable device, but may rather be directlyuploaded or otherwise transmitted to another computing device.

Block 614 includes transmitting the digital output to a computingdevice. Transmitting the digital output may include uploading thedigital output to the computing device via a communications interface,such as communication interface 216 of environmental monitoring system200. The computing device may include a server, a computing network,and/or a cloud computing network. The computing device may be configuredto correlate the digital output with other biometric data, so as to forminferences or provide evidence for the diagnosis of varioushealth-related conditions.

As described elsewhere herein, the wearable device may include at leastone other sensor, which may be configured to obtain other biometricdata. The other biometric data may include, but should not be limitedto, respiration data, movement data, blood pressure data, heart ratedata, blood oxygen saturation data, and galvanic skin response data.

The particular arrangements shown in the Figures should not be viewed aslimiting. It should be understood that other embodiments may includemore or less of each element shown in a given Figure. Further, some ofthe illustrated elements may be combined or omitted. Yet further, anillustrative embodiment may include elements that are not illustrated inthe Figures.

While various examples and embodiments have been disclosed, otherexamples and embodiments will be apparent to those skilled in the art.The various disclosed examples and embodiments are for purposes ofillustration and are not intended to be limiting, with the true scopebeing indicated by the following claims.

What is claimed is:
 1. A method comprising: receiving an audio signal;rectifying and amplifying the audio signal to provide a rectified andlogarithmically amplified signal based on a mathematical log function;sampling the rectified and logarithmically amplified signal to provide asampled rectified and logarithmically amplified signal; converting thesampled rectified and logarithmically amplified signal to a digitaloutput; transmitting the digital output to a computing device, whereinthe computing device is configured to correlate the digital output withother biometric data; and triggering an indication relating to a user'shealth via a user interface, wherein the indication is based on acomparison between the digital output and the other biometric data. 2.The method of claim 1, wherein the rectifying and the amplifying theaudio signal are performed in an analog domain.
 3. The method of claim1, wherein the method is performed by a wearable device.
 4. The methodof claim 3, wherein the wearable device comprises a microphone, whereinreceiving the audio signal is performed by way of the microphone.
 5. Themethod of claim 1, further comprising obtaining the other biometricdata.
 6. The method of claim 5, wherein obtaining the other biometricdata is performed by at least one other sensor.
 7. The method of claim1, wherein the other biometric data comprises at least one of:respiration data, movement data, blood pressure data, heart rate data,blood oxygen saturation data, or galvanic skin response data.
 8. Themethod of claim 1, wherein the amplifying of the audio signal isperformed by a logarithmic amplifier, wherein the logarithmic amplifiercomprises a baseband logarithmic amplifier.
 9. The method of claim 1,wherein the amplifying of the audio signal is performed by a logarithmicamplifier, wherein the logarithmic amplifier comprises a demodulatinglogarithmic amplifier.
 10. The method of claim 1, wherein the rectifyingof the audio signal is performed by a peak detector circuit, wherein thepeak detector circuit comprises a rectifier circuit and a filtercircuit.
 11. A system comprising: analog hardware configured to: providean audio signal; and rectify and logarithmically amplify the audiosignal to provide a rectified and logarithmically amplified signal basedon a mathematical log function; an analog to digital converter (ADC);and a controller comprising a memory and a processor, wherein thecontroller executes instructions stored in the memory so as to carry outoperations, the operations comprising: at predetermined time intervals,causing the ADC to sample the rectified and logarithmically amplifiedsignal and provide a digital output; transmitting the digital output toa computing device, wherein the computing device is configured tocorrelate the digital output with other biometric data; and triggeringan indication relating to a user's health via a user interface, whereinthe indication is based on a comparison between the digital output andthe other biometric data.
 12. The system of claim 11, wherein therectified and logarithmically amplified signal is an analog signal. 13.The system of claim 11, wherein the analog hardware comprises amicrophone configured to provide the audio signal.
 14. The system ofclaim 11, wherein the analog hardware comprises a rectifier and alogarithmic amplifier, wherein the rectifier and the logarithmicamplifier are configured to provide the rectified and logarithmicallyamplified signal.
 15. The system of claim 14, wherein the rectifiercomprises a peak detector circuit, wherein the peak detector circuitcomprises a rectifier circuit and a filter circuit.
 16. The system ofclaim 14, wherein the rectifier comprises a trough detector circuit. 17.The system of claim 14, wherein the logarithmic amplifier comprises abaseband logarithmic amplifier or a demodulating logarithmic amplifier.18. The system of claim 11, further comprising a wearable device,wherein the wearable device comprises at least one other sensor, whereinthe at least one other sensor is configured to obtain the otherbiometric data, and wherein the operations further comprise comparingthe digital output with the other biometric data obtained by the atleast one other sensor.
 19. The system of claim 11, wherein the otherbiometric data comprises at least one of: respiration data, movementdata, blood pressure data, heart rate data, blood oxygen saturationdata, or galvanic skin response data.
 20. The system of claim 11,further comprising a housing, wherein the analog hardware, the ADC, andthe controller are housed within the housing.